Research On The Relation Between Oxygen Uptake And Cardiopulmonary Exercise Capacity During Incremental Exercises Rats

Objective:This study took 25 national secondary male swimmers as the research object,collected 22 items of cardiopulmonary function data through increasing load exercise test,and used a combination of Mantle test and multiple linear regression analysis to investigate the effects of oxygen uptake(VO2)cardiopulmonary function index;using a combination of partial correlation analysis and Bayesian linear regression analysis to analyze cardiopulmonary function parameters that are closely related to maximum oxygen uptake(VO2max),and to screen 4 parameter model combinations with optimal VO2max response.Based on the best four parameter model combinations,multiple linear regression analysis is used to construct a VO2max prediction model,and the VO2max high-response cardiopulmonary function parameter combinations under different model performances are compared and analyzed between models to further explore the cardiopulmonary function parameters that affect VO2max;comprehensive analysis Consistency and difference of VO2 and VO2max influencing factors,providing theoretical basis for daily training,physical fitness monitoring,talent selection,etc.of professional swimmers,and providing scientific support for research on oxygen uptake and maximum oxygen uptake in other endurance sports.Methods:In this study,25 national second-level male swimmers from a college in Shanxi were selected as subjects,and exercise tests were performed through Monark-type power bicycles and Quark b2 cardiopulmonary function test to increase the load until exhaustion,and collected the exercise test process.Among the 22 items of exercise cardiopulmonary function parameters(including VO2),all data are standardized.(1)Resampling the data of each subject standardized to 120 time points according to the time series and deleting at equal intervals,integrating the data of 25 subjects to obtain a data set containing a total of 3000 time points A;According to the grouping criteria of VO2(<1500,[1500,3000),[3000,4000),? 4000,the data set A is divided into 4 groups(Grade 1,Grade2,Grade3,and Grade4);each is analyzed using the Mantle test method.The parameters with significant correlation between VO2 group and VO2(p<0.05)form the corresponding parameter model combination of each group.Based on this,multiple VO2 linear regression analysis methods are used to fit VO2 to obtain 4 VO2 linear regression prediction models;(2)Select 22 items of cardiopulmonary function parameter data corresponding to the VO2max of each subject immediately after exercise test to compose data set B;After using Execel to normalize data set B,use partial correlation analysis to analyze VO2max and 21 other cardiopulmonary functions Correlation analysis was performed to select 11 cardiopulmonary function parameters with significant correlation with VO2max.Based on this,non-exercise parameters such as height,weight and body were combined.The quality index(BMI)and maximum heart rate(HRmax)were analyzed by Bayesian linear regression,and the first four parameter model combinations(Bayes best,Bayes 2nd,Bayes 3rd,and Bayes 4th)with the best Bayesian factors were selected.Multiple linear regression was used to fit VO2max,and four VO2max linear regression prediction models were obtained.The performance of each model was compared to analyze the goodness of fit of each model.The cardiopulmonary function parameters affecting VO2 and VO2max were analyzed,and the similarities and differences of VO2 and VO2max influencing factors were explored.Results:(1)Data set A was grouped based on the VO2 classification standard.Mantle test results showed that the parameters significantly related to VO2 in each group were:Grade 1 group(VE,VCO2,VE/VCO2,VO2/Kg,VO2/HR,and ME?TS),Grade2 group(VE,VCO2,VO2/Kg,VO2/HR and METS),Grade3 group(VCO2,VO2/Kg and V02/HR),Grade4 group(VCO2,VO2/Kg,VO2/HR and METS),four The group contains six cardiopulmonary function parameters of VE,VCO2,VE/VCO2,VO2/Kg,VO2/HR,and METS.Among them,VCO2,VO2/Kg,VO2/HR are included in each group,that is,in each group.Significant correlation with VO2(p<0.05);(2)The performance index values of the four VO2 regression models based on the Mantle test analysis show that the R2 value and adjusted R2 value of the model Grade 1 are greater than the other three groups(Grade 1>Grade2>Grade4>Grade3),the AIC value and BIC value of the model Grade4 are significantly smaller than the other three groups(Grade4<Grade3<Grade 1<Grade2);(3)Based on the results of partial correlation analysis,it reveals that there are 11 sports cardiopulmonary function indexes that are significantly related to VO2max.Including:VE,VCO2,VO2/Kg,VO2/HR,METS,Rf,VT,O2exp,Ti,Te,Ttot;(4)11 items of VO2max display Relevant parameters combined with 4 non-motion parameters were analyzed by Bayesian linear regression to obtain a total of 65535 parameter combinations.The best four parameter model combinations with the best Bayesian factor values were Bayes best(VO2/HR+METS+Weight),Bayes 2nd(VO2/Kg+VO2/HR+Weight),Bayes 3rd(VE+VO2/HR+METS+Weight),Bayes 4th(VE+VO2/Kg+VO2/HR+Weight),the four combinations include VO2/HR,METS,Weight,VO2/Kg,and VE,and each combination contains the parameters VO2/HR and Weight;(5)Multiple linear regression analysis methods were used to linearly simulate each of the four optimal parameter model combinations.Four regression prediction models were obtained by combining VO2max.The model performance indicators showed:R2 value Bayes best=Bayes 2nd>Bayes 3rd=Bayes 4th,adjust R2 value Bayes best>Bayes 2nd>Bayes 3rd=Bayes 4th,RMSE value and MAPE value Bayes 3rd=Bayes 4th>Bayes 2nd=Bayes best,AIC value and BIC value Bayes 3rd>Bayes 4th>Bayes best>Bayes 2nd.Conclusion:(1)The results of correlation analysis show that VE,VO2/Kg,VO2/HR,and METS are significantly correlated with VO2 and VO2max;in addition,VO2 is also significantly correlated with the indicators VCO2 and VE/VCO2;VO2max also has a significant correlation with the indicator Weight;(2)Comparison and analysis of the performance of multiple linear regression models reveals that:VO2 and VO2max are indirect linear relationships with the indicator HR and have a very significant relationship with the inverse of the HR;the indicator Weight The effect on VO2 and VO2max is not direct,but also affected by the oxygen uptake under relative weight;the index VE has a direct linear relationship with VO2 and VO2max;(3)Partial correlation analysis can effectively achieve the initial reduction of the high-dimensional parameters,Bayesian Linear regression analysis has unique advantages for the construction and screening of multi-parameter models;the best prediction model for VO2max is Bayes 3rd:VO2max=-1656.261+3.401� VE+63.628�VO2/HR+141.724�METS+21.915�Weight.It can be used to guide the prediction and practice of maximum oxygen uptake for professional swimmers.